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araffin/mujoco_normalize.py

Created August 18, 2018 08:57
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mujoco_normalize.py
import gym
from stable_baselines.common.policies import MlpPolicy
from stable_baselines.common.vec_env import DummyVecEnv, VecNormalize
from stable_baselines import PPO2
env = DummyVecEnv([lambda: gym.make("Reacher-v2")])
# Automatically normalize the input features
env = VecNormalize(env, norm_obs=True, norm_reward=False,
clip_obs=10.)
model = PPO2(MlpPolicy, env)
model.learn(total_timesteps=2000)
# Don't forget to save the running average when saving the agent
log_dir = "/tmp/"
model.save(log_dir + "ppo_reacher")
env.save_running_average(log_dir)
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